Categorization of Microscopic Wood Images with Transfer Learning Approach on Pretrained Vision Transformer Models
Four Vision Transformer (ViT)-based models were optimized to classify microscopic wood images. The models were DeiT, Google ViT, BeiT, and Microsoft Swin Transformer. Training was performed on a set enriched with data augmentation techniques. The generalization ability of the model was strengthened...
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| Format: | Article |
| Language: | English |
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North Carolina State University
2025-06-01
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| Series: | BioResources |
| Subjects: | |
| Online Access: | https://ojs.bioresources.com/index.php/BRJ/article/view/24722 |
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